Name: Bakari Hamisi Ojiambo
Type: User
Company: Moi University
Bio: A dynamic and passionate Data Science Professional, I bring a track record of success in leveraging statistical modeling, machine learning, and analytics.
Twitter: Bakari_Oj
Location: Kenya
Bakari Hamisi Ojiambo 's Projects
This Repo Contains all the exercise files for Data Science Course of 365 Datascience . The repo is split into the relevant folders & there is one exercise folder which contains all the files of that course. Don't forget to star it :D
I'm now a ALX Student, this is my first repository as a full-stack engineer
Config files for my GitHub profile.
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
Credit Card Fraud Fraud Detection using Classification Algorithms.
The Leek group guide to data sharing
This project focuses on predicting house prices in California using Deep Neural Networks (DNN). The goal is to develop a robust and accurate model that can predict housing prices based on various features, providing valuable insights for real estate stakeholders and potential buyers.
This project aims at predicting insurance medical cost charges using regression techniques.
Excited to share some of the best and most recent machine learning courses available on YouTube.
The purpose of this study is to determine whether height, weight and gender can accurately predict total knee arthroplasty(TKA) sizing.
All the files, notebooks that were used in the various labs in my learning in various platforms including Coursera, IBM, Cognitiveclass.ai
Notebooks for Python for Data Science ranging from beginner introductory topics to more advanced Python concepts and Python Data Science libraries.
The objective is to create the machine learning Model to predict whether a rider will accept, decline or ignore an order sent to them. Here Sendy company is interested to know a specific reaction of a given rider depending on the order requests.
This project applies machine learning techniques to segment TED Talks based on their descriptions. It uses clustering methods and Latent Dirichlet Allocation (LDA) for topic modeling to interpret each cluster.
This project focuses on predicting customer churn in a telecom company, a critical business metric due to the high cost of acquiring new customers compared to retaining existing ones. Using a Kaggle dataset with features like tenure, monthly charges, and types of services used, we aim to build a model that can identify customers likely to cease.
Time Series Analysis of Typhoid Incidences in Nigeria using SARIMA model.
Please see the readme file for more info
This project seeks to analyze the well-being of galaxies given 80 variables that characterize the demographic and socio-economic situation of 181 galaxies over a period of at most 26 years. A composite index is given that measures their well-being.
All course materials for the Zero to Mastery Machine Learning and Data Science course.